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MCP Paradex Server

by sv

paradex_account_transactions

Retrieve filtered transaction history for account reconciliation, auditing trades, and tracking deposits, withdrawals, and funding payments over time.

Instructions

Get account transaction history.

Retrieves a filtered history of account transactions, including deposits,
withdrawals, trades, funding payments, and other account activities.
Use transaction_type and time filters to limit the results and avoid
overwhelming the client.

This tool is valuable for:
- Reconciliation of account activity
- Auditing trading history
- Tracking deposits and withdrawals
- Analyzing funding payments over time

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transaction_typeNoFilter by transaction type.
start_unix_msYesStart time in unix milliseconds.
end_unix_msYesEnd time in unix milliseconds.
limitNoMaximum number of transactions to return.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main handler function for the 'paradex_account_transactions' tool, decorated with @server.tool for registration. It fetches transactions using the authenticated Paradex client, validates with TypeAdapter, and formats the response with schema information.
    @server.tool(name="paradex_account_transactions")
    async def get_account_transactions(
        transaction_type: Annotated[
            str | None, Field(default=None, description="Filter by transaction type.")
        ],
        start_unix_ms: Annotated[int, Field(description="Start time in unix milliseconds.")],
        end_unix_ms: Annotated[int, Field(description="End time in unix milliseconds.")],
        limit: Annotated[
            int, Field(default=50, description="Maximum number of transactions to return.")
        ],
        ctx: Context = None,
    ) -> list[Transaction]:
        """
        Get account transaction history.
    
        Retrieves a filtered history of account transactions, including deposits,
        withdrawals, trades, funding payments, and other account activities.
        Use transaction_type and time filters to limit the results and avoid
        overwhelming the client.
    
        This tool is valuable for:
        - Reconciliation of account activity
        - Auditing trading history
        - Tracking deposits and withdrawals
        - Analyzing funding payments over time
    
        """
        client = await get_authenticated_paradex_client()
        params = {
            "type": transaction_type,
            "start_at": start_unix_ms,
            "end_at": end_unix_ms,
            "limit": limit,
        }
        # Remove None values from params
        params = {k: v for k, v in params.items() if v is not None}
        response = client.fetch_transactions(params)
        if "error" in response:
            await ctx.error(response)
            raise Exception(response["error"])
        transactions = transaction_adapter.validate_python(response["results"])
        results = {
            "description": Transaction.__doc__.strip() if Transaction.__doc__ else None,
            "fields": Transaction.model_json_schema(),
            "results": transactions,
        }
        return results
  • Pydantic model defining the structure and validation for Transaction objects, used in the tool's output schema.
    class Transaction(BaseModel):
        """Transaction model representing an account transaction on Paradex."""
    
        id: Annotated[
            str, Field(description="Unique string ID of the event that triggered the transaction")
        ]
        type: Annotated[str, Field(description="Event that triggered the transaction")]
        hash: Annotated[str, Field(description="Tx Hash of the settled trade")]
        state: Annotated[str, Field(description="Status of the transaction on Starknet")]
        created_at: Annotated[
            int, Field(description="Timestamp from when the transaction was sent to blockchain gateway")
        ]
        completed_at: Annotated[
            int, Field(description="Timestamp from when the transaction was completed")
        ]
  • The @server.tool decorator registers the tool with the MCP server.
    @server.tool(name="paradex_account_transactions")
  • TypeAdapter for list[Transaction] used for input validation and serialization in the handler.
    transaction_adapter = TypeAdapter(list[Transaction])
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that this retrieves filtered history and mentions avoiding overwhelming results, which hints at potential data volume issues. However, it doesn't cover important behavioral aspects like whether this is a read-only operation, authentication requirements, rate limits, pagination behavior, or error conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear purpose statement followed by elaboration, usage guidance, and bulleted use cases. Each sentence adds value, though the bulleted list could be more concise. The information is appropriately front-loaded with the core functionality stated first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that an output schema exists (so return values are documented elsewhere), 100% schema coverage, and no complex nested objects, the description provides adequate context. It covers purpose, usage guidance, and valuable applications. The main gap is lack of behavioral transparency details that would be important for a tool accessing transaction history.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description mentions using 'transaction_type and time filters' which aligns with the schema parameters, but adds no additional semantic context beyond what's in the schema. The baseline score of 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get account transaction history' and elaborates on what types of transactions are included (deposits, withdrawals, trades, funding payments). It distinguishes this tool from siblings like paradex_account_funding_payments by covering multiple transaction types, but doesn't explicitly contrast with paradex_account_fills or paradex_orders_history which might overlap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool: 'Use transaction_type and time filters to limit the results and avoid overwhelming the client.' It also lists valuable use cases (reconciliation, auditing, tracking, analyzing). However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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